Wude Xie , Zhaoyang Jiang , Lu Wang , Zhenlin Liang
{"title":"Hydrodynamic responses of a large flexible net swinging in waves","authors":"Wude Xie , Zhaoyang Jiang , Lu Wang , Zhenlin Liang","doi":"10.1016/j.aquaeng.2024.102491","DOIUrl":"10.1016/j.aquaeng.2024.102491","url":null,"abstract":"<div><div>In deep-sea aquaculture cages, large flexible nets are usually mounted on the steel frames of aquaculture cages, which are easily broken. When a cage vibrates over time, the flexible nets also oscillate, causing relative motions with respect to fluid flows. This study focuses on the hydrodynamic behaviors of a large flexible net swinging in waves, in which three different types of swings are simulated with the swing center located above, on, and below the net, respectively. The incoming waves are simulated using the Airy wave theory. The nonlinear vibrations of the flexible net in three dimensions are solved using the lumped-mass method. The influences of swing amplitudes and frequencies on the vibrations of the net are analyzed in detail. It can be known that with the increase of swing amplitude, the vibration displacements of the net in the horizontal direction decrease, while they increase in the vertical direction. Furthermore, the dynamic tensions of net twines increase as the swing angular frequency rises.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"108 ","pages":"Article 102491"},"PeriodicalIF":3.6,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142653199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A robotic fish processing line enhanced by machine learning","authors":"Sangam Mainali, Cheryl Li","doi":"10.1016/j.aquaeng.2024.102481","DOIUrl":"10.1016/j.aquaeng.2024.102481","url":null,"abstract":"<div><div>This paper presents the design of a comprehensive automatic fish processing line utilizing machine learning algorithms. The processing line encompasses several essential steps, including fish identification by type, fish sorting by size, fish orientation based on shape, and fish cutting at the optimal chopping points. The primary objective of this design is not just automation but also maximizing economic benefits by preserving the maximum amount of fish meat during the cutting process, achieved through the application of machine learning algorithms. To accomplish these goals, we employ a combination of transfer learning and convolutional neural networks to establish criteria for actions across all stages of automatic fish processing. At the heart of the processing station is a conveyor belt equipped with numerous sensors and lenses. Positioned along this conveyor belt are two robotic arms, responsible for precise positioning and cutting operations, all guided by the machine learning algorithms. To provide a visual representation of these design concepts, we have created a 3D SolidWorks model.</div></div>","PeriodicalId":8120,"journal":{"name":"Aquacultural Engineering","volume":"108 ","pages":"Article 102481"},"PeriodicalIF":3.6,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142653197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}